Correlation Between UJU Electronics and Sungchang Autotech
Can any of the company-specific risk be diversified away by investing in both UJU Electronics and Sungchang Autotech at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining UJU Electronics and Sungchang Autotech into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between UJU Electronics Co and Sungchang Autotech Co, you can compare the effects of market volatilities on UJU Electronics and Sungchang Autotech and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in UJU Electronics with a short position of Sungchang Autotech. Check out your portfolio center. Please also check ongoing floating volatility patterns of UJU Electronics and Sungchang Autotech.
Diversification Opportunities for UJU Electronics and Sungchang Autotech
0.56 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between UJU and Sungchang is 0.56. Overlapping area represents the amount of risk that can be diversified away by holding UJU Electronics Co and Sungchang Autotech Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Sungchang Autotech and UJU Electronics is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on UJU Electronics Co are associated (or correlated) with Sungchang Autotech. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Sungchang Autotech has no effect on the direction of UJU Electronics i.e., UJU Electronics and Sungchang Autotech go up and down completely randomly.
Pair Corralation between UJU Electronics and Sungchang Autotech
Assuming the 90 days trading horizon UJU Electronics Co is expected to generate 1.37 times more return on investment than Sungchang Autotech. However, UJU Electronics is 1.37 times more volatile than Sungchang Autotech Co. It trades about 0.02 of its potential returns per unit of risk. Sungchang Autotech Co is currently generating about -0.11 per unit of risk. If you would invest 1,566,000 in UJU Electronics Co on September 27, 2024 and sell it today you would earn a total of 10,000 from holding UJU Electronics Co or generate 0.64% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
UJU Electronics Co vs. Sungchang Autotech Co
Performance |
Timeline |
UJU Electronics |
Sungchang Autotech |
UJU Electronics and Sungchang Autotech Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with UJU Electronics and Sungchang Autotech
The main advantage of trading using opposite UJU Electronics and Sungchang Autotech positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if UJU Electronics position performs unexpectedly, Sungchang Autotech can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Sungchang Autotech will offset losses from the drop in Sungchang Autotech's long position.UJU Electronics vs. Dongil Technology | UJU Electronics vs. KG Eco Technology | UJU Electronics vs. Digital Imaging Technology | UJU Electronics vs. Guyoung Technology Co |
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Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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